The ability of an organism to regulate the expression of its genes is of central importance to life. A breakdown in this homeostasis leads to disease states, such as cancer, where a cell multiplies uncontrollably, to the detriment of the organism. The general mechanisms utilized by organisms to maintain this gene expression homeostasis are the focus of intense scientific study.
It recently has been discovered that some cells are able to down-regulate their gene expression through certain ribonucleic acid (RNA) molecules. Namely, when RNA molecules are in contact with certain of the cells' protein machinery they act as potent gene translation inhibitors, also referred to as post-transcriptional gene silencing mechanisms. This process, which is known as RNA interference, or RNAi, has been found to function both in mediating resistance to endogenous and exogenous pathogenic nucleic acids, as well as, in regulating the expression of genes inside cells.
The term ‘gene expression,’ as used herein, refers generally to the transcription of messenger-RNA (mRNA) from a gene, and, e.g., its subsequent translation into a functional protein. One class of RNA molecules involved in gene expression regulation comprises microRNAs, which are endogenously encoded and regulate gene expression by either disrupting the translation process or by degrading mRNA transcripts, e.g., inducing post-transcriptional repression of one or more target sequences. Currently, hundreds of microRNAs exist for many genomes. However, only a handful of targets have been identified for only a small number of microRNAs.
The RNAi/post-transcriptional gene silencing mechanism allows an organism to employ short RNA sequences to either degrade or disrupt translation of mRNA transcripts containing a complementary or near-complementary sequence. Early studies suggested only a limited role for RNAi, that of a defense mechanism against foreign born pathogens. However, the subsequent discovery of many endogenously-encoded microRNAs pointed towards the possibility of this being a more general, in nature, control mechanism. Recent evidence has led the community to hypothesize that a wider spectrum of biological processes are affected by RNAi, thus extending the range of this presumed control layer. Despite being the focus of intense research investment, the manner in which a particular microRNA determines its specific gene target and exerts its control over the latter remains largely an open question. The magnitude of this problem has led experimentalists to rely increasingly upon computational methods as a source of guidance.
To date, the published computational methods for microRNA target site detection have been varied. One group of approaches employs modified versions of the dynamic programming solution to the local suffix alignment problem. A second group of methods is “signature-based” with the signature derived from the first 6-8 consecutive nucleotides in the 5′ region (“seed region”) of the microRNA. The methods employ this ‘signature’ explicitly as well as implicitly. Other schemes use hidden Markov models to find seed matches or are based on exhaustive schemes that calculate interactions for every offset of the target sequence of the microRNA and sub-select those of the relative placements which are deemed significant according to a specific statistical measure. Despite their methodological variety and the fact that the underlying computational methods can be applied to genomes in isolation, the majority of these approaches use the conservation of a potential binding site at orthologous positions across multiple species as a filtering criterion before they report any results.
In recent years, predictions made by many of these methods have been validated by experiments. Nonetheless, the number of confirmed microRNA/mRNA complexes remains very small by comparison. This underscores the inherent difficulty of the task and the need for continuing research in computational approaches that can address the problem at hand.
A better understanding of the mechanism of the RNA interference process would benefit the fight against disease, drug design and host defense mechanisms.